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All Journal JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Informatika, Komputasi, Aplikasi & Bisnis (INFOKABIN)
Ahmad Latif
Universitas Komputama
Computer Science & IT Education

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Perancangan Sistem Informasi Pemesanan Tiket Wisata Alam De' Balong Assaeida Berbasis Website Ahmad Latif; Muhtyas Yugi; Imam imam
INFOKABIN (Informatika, Komputasi, Aplikasi dan Bisnis) Vol 1 No 1 (2026): Januari 2026
Publisher : Universitas Al-Irsyad Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36760/ifkb.v1i1.713

Abstract

designed to provide convenience for visitors in booking tickets and accessing park information online. Simultaneously, it assists management in generating accurate sales and visitor reports. The website was developed using the Waterfall method, utilizing tools such as HTML, Cascading Style Sheets (CSS), PHP, MySQL Database, and the Bootstrap framework. The results of this study conclude that the implementation of a web-based information system optimizes transaction operations and reporting management at De' Balong Assaeida. Kata Kunci/Keywords: Information Systems, Ticket Reservation, De' Balong Assaeida., Metode Waterfall, Website. ABSTRAK Pesatnya perkembangan teknologi informasi mendorong kebutuhan akses data yang cepat dan efisien, termasuk dalam sektor pariwisata. Penelitian ini bertujuan untuk merancang sistem informasi pemesanan tiket berbasis website pada Taman Wisata De' Balong Assaeida. Peralihan dari sistem tiket fisik ke transaksi elektronik diharapkan dapat meningkatkan efektivitas layanan serta memperluas jangkauan promosi melalui internet. Sistem ini dirancang untuk memberikan kemudahan bagi pengunjung dalam memesan tiket dan mengakses informasi taman secara daring. Di sisi lain, sistem ini mempermudah pihak pengelola dalam mengelola laporan penjualan dan data pengunjung secara akurat. Pengembangan website ini menggunakan metode Waterfall dengan alat pendukung berupa HTML, Cascading Style Sheet (CSS), PHP, Database MySQL, serta framework Bootstrap. Hasil penelitian ini menyimpulkan bahwa implementasi sistem informasi berbasis web mampu mengoptimalkan operasional transaksi dan manajemen pelaporan pada Taman Wisata De' Balong Assaeida.
COMPARISON OF THE PERFORMANCE OF SVM, RANDOM FOREST, AND NEURAL NETWORK ALGORITHMS IN SENTIMENT ANALYSIS OF OPENAI APPLICATION REVIEWS ON THE GOOGLE PLAY STORE Ahmad Latif; Muhtyas Yugi; Fandy Setyo Utomo; Taqwa Hariguna
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 11, No 1 (2026)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v11i1.7793

Abstract

This study compares the performance of three machine learning algo-rithms—Support Vector Machine (SVM), Random Forest (RF), and Neural Network (NN)—in sentiment analysis of user reviews for the OpenAI application on the Google Play Store. The primary objective of this study is to evaluate the effectiveness of each algorithm in clas-sifying user reviews into three sentiment categories: positive, negative, and neutral. The dataset used consists of user reviews of the OpenAI application, collected directly from the Google Play Store. Model per-formance was evaluated using accuracy, precision, recall, and F1-score metrics. The results indicate that the Neural Network algorithm achieved the best overall performance in terms of accuracy and F1-score. SVM demonstrated competitive performance, particularly in classifying positive and neutral sentiments, while Random Forest showed an advantage in terms of precision but performed lower over-all, especially in classifying negative sentiments. Therefore, the Neural Network is considered the most effective algorithm for sentiment analysis tasks in this study
Co-Authors Fandy Setyo Utomo Imam Imam Muhtyas Yugi Muhtyas Yugi Taqwa Hariguna